I am a Lecturer in Economics at the University of Sussex, where I joined the Department of Economics in September 2020. Before that, I was a postdoctoral researcher at the University of Amsterdam. In May 2019, I completed my PhD at the University of Amsterdam and the Tinbergen Institute, under supervision of Cars Hommes and Joep Sonnemans.

My main research fields are behavioral and experimental economics, with a focus on experimental macroeconomics and finance. I make use of controlled laboratory experiments to study the interactions between individual behavior in market settings (e.g. price expectations or production decisions) and the resulting market outcomes (e.g. asset or commodity prices). My experimental studies can be used to validate and develop behavioral models, and to design and test policy interventions.


View CV in PDF

Please see my CV for more information about my education, research and teaching experience.

My academic references are:
Prof. Cars Hommes, University of Amsterdam (
Prof. Joep Sonnemans, University of Amsterdam (
Prof. John Duffy, University of California, Irvine (
Prof. Nobuyuki Hanaki, Osaka University (


Managing bubbles in experimental asset markets with monetary policy

(with Cars Hommes – forthcoming in Journal of Money, Credit and Banking)
Link to paper

We study the effect of a "leaning against the wind" monetary policy on asset price bubbles in a learning-to-forecast experiment, where prices are driven by the expectations of market participants. We find that a strong interest rate response is successful in preventing or deflating large price bubbles, while a weak response is not. Giving information about the interest rate changes and communicating the goal of the policy increases coordination of expectations and has a stabilizing effect. When the steady state fundamental price is unknown and the interest rate rule is based on a proxy instead, the policy is less effective.

Coordination on bubbles in large-group asset pricing experiments

(with Te Bao, Cars Hommes and Domenico Massaro; Journal of Economic Dynamics and Control  2020, 110: 103702)
Link to paper

We present a large-group experiment in which participants predict the price of an asset, whose realization depends on the aggregation of individual forecasts. The markets consist of 21 to 32 participants, a group size larger than in most experiments. Multiple large price bubbles occur in six out of seven markets. The bubbles emerge even faster than in smaller markets. Individual forecast errors do not cancel out at the aggregate level, but participants coordinate on a trend-following prediction strategy that gives rise to large bubbles. The observed price patterns can be captured by a behavioral heuristics switching model with heterogeneous expectations.

Working Papers

Experiences and expectations in asset markets: an experimental study

Link to latest version

This paper presents experimental evidence that experienced price patterns in asset markets have a large impact on expectations and thereby affect the (de)stabilization of asset prices in the future. In a controlled learning-to-forecast experiment, subjects first experience a stable or a bubbly asset market before entering into a same- or mixed-experience market. In markets where all subjects experienced stability, convergence to the fundamental price is faster. Bubble formation is faster in markets where all subjects experienced bubbles. In mixed-experience markets, dynamics can go both ways: prices either stabilize or destabilize. Heterogeneity in expectations is larger when more subjects have experienced bubbles before.

Planar learning-to-forecast market games

(with Cars Hommes and Eva Leveltwork in progress: preparing manuscript)

In this project, we investigate how expectation formation in a two-dimensional market experiment depends on the eigenvalues of the underlying model. A motivating example of such a model is the New Keynesian framework. Our results suggest that eigenvalues can be used as predictors for the stability of equilibria. In the case of positive real eigenvalues we observe a change from stable to unstable dynamics inside the unit circle. Complex eigenvalues result in more stable dynamics than their real counterparts. We compare our findings to various theories of expectation formation and develop a more sophisticated two-dimensional version of the heuristics switching model to explain the observed dynamics.

Import tariffs in coupled cobweb markets

(with Dávid Kopányi, Jan Tuinstra and Frank Westerhoffwork in progress: preparing manuscript)

Although free trade is typically believed to maximize allocative efficiency, a decrease in barriers to trade is not necessarily welfare enhancing. Recent theoretical work on coupled cobweb markets has shown that switching between markets by firms may lead to instability and perpetual price fluctuations that are detrimental to welfare and that do not occur when these markets are isolated. Our experiment empirically tests the effect of import tariffs on price volatility and welfare in coupled cobweb markets. Subjects play the role of firms and decide on how much to supply in their home country and abroad; an import tariff τ is charged on units sold abroad. We consider four treatments: free trade (τ=0%), two levels of import tariffs (τ=20% and τ=30%), and autarky (τ=80%). Our results suggest that a reduction in tariffs indeed increases price volatility in both markets, and we can reject the prediction that total surplus increases as tariffs decrease.

Online 30-day asset market experiment

(with Cars Hommes, Anita Kopányi-Peuker and Joep Sonnemanswork in progress: preparing experiment)

We plan to run a large-scale online asset market learning-to-forecast experiment, in which subjects predict the price of an asset on the next day for 30 consecutive days. The realized price is based on the prediction of all subjects in a certain market, and subjects are paid according to forecasting accuracy. The aim of this project is threefold. First, the online setup allows us to form exceptionally large markets of 250 subjects, which we compare to small markets of 15 subjects. Second, we investigate whether spanning the experiment over multiple days affects forecasts and market dynamics, compared to typical 2-hour lab experiments. Third, we gain experience with and thereby explore the possibilities for conducting large-scale incentivized group experiments.


Department of Economics, University of Sussex Business School
Jubilee Building 261
University of Sussex
United Kingdom